Publication bias in ecology and evolution: an empirical assessment using the 'trim and fill' method

Recent reviews of specific topics, such as the relationship between male attractiveness to females and fluctuating asymmetry or attractiveness and the expression of secondary sexual characters, suggest that publication bias might be a problem in ecology and evolution. In these cases, there is a significant negative correlation between the sample size of published studies and the magnitude or strength of the research findings (formally the ‘effect size’). If all studies that are conducted are equally likely to be published, irrespective of their findings, there should not be a directional relationship between effect size and sample size; only a decrease in the variance in effect size as sample size increases due to a reduction in sampling error. One interpretation of these reports of negative correlations is that studies with small sample sizes and weaker findings (smaller effect sizes) are less likely to be published. If the biological literature is systematically biased this could undermine the attempts of reviewers to summarise actual biology relationships by inflating estimates of average effect sizes. But how common is this problem? And does it really effect the general conclusions of literature reviews? Here, we examine data sets of effect sizes extracted from 40 peer‐reviewed, published meta‐analyses. We estimate how many studies are missing using the newly developed ‘trim and fill’ method. This method uses asymmetry in plots of effect size against sample size (‘funnel plots’) to detect ‘missing’ studies. For random‐effect models of meta‐analysis 38% (15/40) of data sets had a significant number of ‘missing’ studies. After correcting for potential publication bias, 21% (8/38) of weighted mean effects were no longer significantly greater than zero, and 15% (5/34) were no longer statistically robust when we used random‐effects models in a weighted meta‐analysis. The mean correlation between sample size and the magnitude of standardised effect size was also significantly negative (r_s=‐0.20, P < 0‐0001). Individual correlations were significantly negative (P < 0.10) in 35% (14/40) of cases. Publication bias may therefore effect the main conclusions of at least 15–21% of meta‐analyses. We suggest that future literature reviews assess the robustness of their main conclusions by correcting for potential publication bias using the ‘trim and fill’ method.     

Estimating genetic benefits of polyandry from experimental studies: a meta‐analysis

The consequences of polyandry for female fitness are controversial. Sexual conflict studies and a meta‐analysis of mating rates in insects suggest that there is a longevity cost when females mate repeatedly. Even so, compensatory material benefits can elevate egg production and fertility, partly because polyandry ensures an adequate sperm supply. Polyandry can therefore confer direct benefits. The main controversy surrounds genetic benefits. The argument is analogous to that surrounding the evolution of conventional female mate choice, except that with polyandry it is post‐copulatory mechanisms that might bias paternity towards males with higher breeding values for fitness. Recent meta‐analyses of extra‐pair copulations in birds have cast doubt on whether detectable genetic benefits exist. By contrast, another meta‐analysis showed that polyandry elevates egg hatching success (possibly due to a fertilization bias towards sperm with paternal genes that elevate embryo survival) in insects. A detailed summary of whether polyandry elevates other components of offspring performance is lacking. Here we present a comprehensive meta‐analysis of 232 effect sizes from 46 experimental studies. These experiments were specifically designed to try to quantify the potential genetic benefits of polyandry by controlling fully for the number of matings by females assigned to monandry and polyandry treatments. The bias‐corrected 95% confidence intervals for egg hatching success (d = ?0.01 to 0.61), clutch production (d = 0.07 to 0.45) and fertility (d = 0.04 to 0.40) all suggest that polyandry has a beneficial effect (although P values from parametric tests were marginally non‐significant at P = 0.075, 0.052 and 0.058, respectively). Polyandry was not significantly beneficial for any single offspring performance trait (e.g. growth rate, survival, adult size), but the test power was low due to small sample sizes (suggesting that many more studies are still needed). We then calculated a composite effect size that provides an index of general offspring performance. Depending on the model assumptions, the mean effect of polyandry was either significantly positive or marginally non‐significant. A possible role for publication bias is discussed. The magnitude of the reported potential genetic benefits (d = 0.07 to 0.19) are larger than those from two recent meta‐analyses comparing offspring sired by social and extra‐pair mates in birds (d = 0.02 to 0.04). This difference raises the intriguing possibility that cryptic, post‐copulatory female choice might be more likely to generate ‘good gene’ or ‘compatible gene’ benefits than female choice of mates based on the expression of secondary sexual traits.     

Ignoring non‐English‐language studies may bias ecological meta‐analyses

Meta‐analysis plays a crucial role in syntheses of quantitative evidence in ecology and biodiversity conservation. The reliability of estimates in meta‐analyses strongly depends on unbiased sampling of primary studies. Although earlier studies have explored potential biases in ecological meta‐analyses, biases in reported statistical results and associated study characteristics published in different languages have never been tested in environmental sciences. We address this knowledge gap by systematically searching published meta‐analyses and comparing effect‐size estimates between English‐ and Japanese‐language studies included in existing meta‐analyses. Of the 40 published ecological meta‐analysis articles authored by those affiliated to Japanese institutions, we find that three meta‐analysis articles searched for studies in the two languages and involved sufficient numbers of English‐ and Japanese‐language studies, resulting in four eligible meta‐analyses (i.e., four meta‐analyses conducted in the three meta‐analysis articles). In two of the four, effect sizes differ significantly between the English‐ and Japanese‐language studies included in the meta‐analyses, causing considerable changes in overall mean effect sizes and even their direction when Japanese‐language studies are excluded. The observed differences in effect sizes are likely attributable to systematic differences in reported statistical results and associated study characteristics, particularly taxa and ecosystems, between English‐ and Japanese‐language studies. Despite being based on a small sample size, our findings suggest that ignoring non‐English‐language studies may bias outcomes of ecological meta‐analyses, due to systematic differences in study characteristics and effect‐size estimates between English‐ and non‐English languages. We provide a list of actions that meta‐analysts could take in the future to reduce the risk of language bias.     

Parasitism of cotton leafworm Alabama argillacea eggs by Trichogramma pretiosum in commercial cotton fields

Release of natural enemies in commercial fields is challenging and has been inconsistent in the results achieved. This work discusses the augmentative releases of Trichogramma pretiosum to control the cotton leafworm (CLW) Alabama argillacea and also examines the parasitoid–host interaction under grower field conditions. The treatments consisted of fields with and without releases of T. pretiosum set up in Primavera do Leste and Campo Verde Counties, MT, Brazil, during three different seasons (2003 and 2004 dry and 2004 regular summer seasons). Trichogramma wasps were weekly released in the treated fields throughout the entire sampling period (14–15 week period) at a rate of 100 000 wasps per hectare. One‐way repeated measures analysis of variance was performed for the number of parasitized eggs, followed by a meta‐analysis procedure to determine the contribution of T. pretiosum release on overall parasitism. In addition, regression analysis was conducted with each season’s data sets to study the relationship of the host density and parasitism response by T. pretiosum. The overall results of Trichogramma augmentative releases did not result in significant increase of CLW egg parasitism beyond the natural parasitism in the areas studied. However, based on Cohen’s d effect sizes from the meta‐analysis, the parasitism rate was greater in fields under T. pretiosum releases during four out of 15 weeks surveyed. The parasitism of CLW eggs by T. pretiosum exhibited host density‐dependence only in one out of three seasons surveyed. These findings are encouraging as they are evidence that T. pretiosum is able to maintain a considerable level of parasitism under commercial field conditions, highlighting their potential value in large‐scale commercial areas of cotton as previously found at the small and diverse farming scale. Future studies should address the potential of early‐season, low density releases of the parasitoid.     

Formalizing the definition of meta‐analysis in Molecular Ecology

Meta‐analysis, the statistical synthesis of pertinent literature to develop evidence‐based conclusions, is relatively new to the field of molecular ecology, with the first meta‐analysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta‐analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta‐analyses previously published in this journal. We also provide a brief overview of the many components required for meta‐analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's F_ST and its related analogues as effect sizes in meta‐analysis. We performed a literature review to identify articles published as ‘meta‐analyses’ in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta‐analyses published in Molecular Ecology have the potential to set the standard for meta‐analyses in other journals. We found that while many of these reviewed articles were strong meta‐analyses, others failed to follow standard meta‐analytical techniques. One of these unsatisfactory meta‐analyses was in fact a secondary analysis. Other studies attempted meta‐analyses but lacked the fundamental statistics that are considered necessary for an effective and powerful meta‐analysis. By drawing attention to the inconsistency of studies labelled as meta‐analyses, we emphasize the importance of understanding the components of traditional meta‐analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology.     

A novel meta‐analytical approach to improve systematic review of rates and patterns of microevolution

A classic topic in ecology and evolution, phenotypic microevolution of quantitative traits has received renewed attention in the face of rapid global environmental change. However, for plants, synthesis has been hampered by the limited use of standard metrics, which makes it difficult to systematize empirical information. Here we demonstrate the advantages of incorporating meta‐analysis tools to the review of microevolutionary rates. We perform a systematic survey of the plant literature on microevolution of quantitative traits over known periods of time, based on the scopus database. We quantify the amount of change by standard mean difference and develop a set of effect sizes to analyze such data. We show that applying meta‐analysis tools to a systematic literature review allows the extraction of a much larger volume of information than directly calculating microevolutionary rates. We also propose derived meta‐analysis effect sizes (h, LG and LR) which are appropriate for the study of evolutionary patterns, the first being similar to haldanes, the second and third allowing the application of a preexisting analytical framework for the inference of evolutionary mechanisms. This novel methodological development is applicable to the study of microevolution in any taxa. To pilot test it, we built an open‐access database of 1,711 microevolutionary rates of 152 angiosperm species from 128 studies documenting population changes in quantitative traits following an environmental novelty with a known elapsed time (<260 years). The performance of the metrics proposed (h, LG and LR) is similar to that of preexisting ones, and at the same time they bring the advantages of lower estimation bias and higher number of usable observations typical of meta‐analysis.     

Sexual selection and sperm quantity: meta‐analyses of strategic ejaculation

Multiple mating or group spawning leads to post‐copulatory sexual selection, which generally favours ejaculates that are more competitive under sperm competition. In four meta‐analyses we quantify the evidence that sperm competition (SC) favours greater sperm number using data from studies of strategic ejaculation. Differential investment into each ejaculate emerges at the individual level if males exhibit phenotypic plasticity in ejaculate properties in response to the likely risk and/or intensity of sperm competition after a given mating. Over the last twenty years, a series of theoretical models have been developed that predict how ejaculate size will be strategically adjusted in relation to: (a) the number of immediate rival males, with a distinction made between 0 versus 1 rival (‘risk’ of SC) and 1 versus several rivals (‘intensity’ of SC); (b) female mating status (virgin or previously mated); and (c) female phenotypic quality (e.g. female size or condition). Some well‐known studies have reported large adjustments in ejaculate size depending on the relevant social context and this has led to widespread acceptance of the claim that strategic sperm allocation occurs in response to each of these factors. It is necessary, however, to test each claim separately because it is easy to overlook studies with weak or negative findings. Compiling information on the variation in outcomes among species is potentially informative about the relevance of these assumptions in different taxa or mating systems. We found strong evidence that, on average, males transfer larger ejaculates to higher quality females. The effect of female mating status was less straightforward and depended on how ejaculate size was measured (i.e. use of proxy or direct measure). There is strong evidence that ejaculate size increased when males were exposed to a single rival, which is often described as a response to the risk of SC. There is, however, no evidence for the general prediction that ejaculate size decreases as the number of rivals increases from one to several males (i.e. in response to a higher intensity of SC which lowers the rate of return per sperm released). Our results highlight how meta‐analysis can reveal unintentional biases in narrative literature reviews. We note that several assumptions of theoretical models can alter an outcome's predicted direction in a given species (e.g. the effect of female mating status depends on whether there is first‐ or last‐male sperm priority). Many studies do not provide this background information and fail to make strong a priori predictions about the expected response of ejaculate size to manipulation of the mating context. Researchers should be explicit about which model they are testing to ensure that future meta‐analyses can better partition studies into different categories, or control for continuous moderator variables.     

EVIDENCE FOR IMPACTS OF NONINDIGENOUS MACROALGAE: A META‐ANALYSIS OF EXPERIMENTAL FIELD STUDIES1

Invasions by nonindigenous macroalgal species (NIMS) potentially cause severe impacts on native species. We conducted a meta‐analysis of 18 field‐based manipulative experiments to quantify the direction and magnitude of impacts (Hedges effect size d, hereafter ES). We found significant small‐to‐medium negative effects on “macrophyte abundance” (cover, biomass of native taxa; ES_cumulative = ?0.30) and medium‐to‐large negative effects on “macrophyte assemblages” (richness, diversity, total abundance; ES_cumulative = ?0.70). In contrast, ES_cumulative were not significant for “macrophyte processes” (growth, mortality; ES_cumulative = ?0.39), “animal abundance” (densities; ES_cumulative = ?0.13), or “animal assemblages” (richness, diversity; ES_cumulative = 0.75). The nonsignificant effect sizes were characterized by low sample sizes and should be interpreted with caution. Three study‐specific effect sizes were particularly large (cumulative are likely biased toward larger effects because only the most conspicuous NIMS have been tested and because nonsignificant results are less likely to be published. To better understand the impacts of NIMS, more manipulative experiments are needed, testing more species and under contrasting environmental conditions. Future studies should include procedural control treatments and report the abundance of the NIMS to avoid ambiguous interpretations. In conclusion, current experimental evidence shows that NIMS have, on average, small‐to‐large negative impacts on native plant species and assemblages. It is possible that these effects can result in severe consequences when accumulated over long time periods and large spatial scales.     

What do we really know about the signalling role of plumage colour in blue tits? A case study of impediments to progress in evolutionary biology

Evolutionary biologists seek to explain the origin and maintenance of phenotypes, and a substantial portion of this research is accomplished by thorough study of individual species. For instance, many researchers study individual species to understand evolution of ornamental traits which appear to be products of sexual selection. I explored our understanding of sexual ornaments in a well‐studied vertebrate species that may serve as a case study for research programs in evolutionary biology. I attempted to located all published papers examining plumage colour and variables related to sexual selection hypotheses in a common European songbird, the blue tit (Cyanistes caeruleus). Researchers have estimated over 1200 statistical relationships with plumage colour of blue tits in 52 studies. However, of the approximately 1000 main‐effect relationships from the 48 studies that are candidates for inclusion in this meta‐analysis, more than 400 were reported without details of strength and direction. Circumstantial evidence suggests that an unknown number of other estimated effects remain unpublished. Missing information is a substantial barrier to interpretation of these papers and to meta‐analytic synthesis. Examination and analysis of funnel plots indicated that unpublished effects may be a biased sample of all effects, especially for comparisons of plumage colour to age and individual quality, and possibly also to measures of mate choice. Further, type I error was likely elevated by the large number of statistical comparisons evaluated, the frequent use of iterative model‐building procedures, and a willingness to interpret a wide variety of results as support for a hypothesis. Type I errors were made more problematic because blue tit plumage researchers only rarely have attempted to replicate important findings in their own work or that of others. Replication is essential to drawing robust scientific conclusions, especially in probabilistic systems with moderate to weak effects or a likelihood of bias. Last, researchers studying blue tit plumage have often developed ad hoc explanations for deviations of results from their predictions. Revising hypotheses in light of data is appropriate, but these revised hypotheses were rarely tested with new data. The only highly robust conclusion supported by meta‐analysis is that male blue tits have plumage that reflects more light in the ultraviolet and yellow wavelengths than the plumage of females. Various other effects, including condition‐dependence of plumage colour expression and a tendency for females to adjust the sex ratio of their offspring in response to male colour, remain uncertain. These obstacles to progress in the blue tit plumage literature are likely common in evolutionary biology, and so I recommend changes to incentive structures which may improve progress towards scientific understanding in this discipline.     

Multivariate meta‐analysis with an increasing number of parameters

Meta‐analysis can average estimates of multiple parameters, such as a treatment's effect on multiple outcomes, across studies. Univariate meta‐analysis (UVMA) considers each parameter individually, while multivariate meta‐analysis (MVMA) considers the parameters jointly and accounts for the correlation between their estimates. The performance of MVMA and UVMA has been extensively compared in scenarios with two parameters. Our objective is to compare the performance of MVMA and UVMA as the number of parameters, p, increases. Specifically, we show that (i) for fixed‐effect (FE) meta‐analysis, the benefit from using MVMA can substantially increase as p increases; (ii) for random effects (RE) meta‐analysis, the benefit from MVMA can increase as p increases, but the potential improvement is modest in the presence of high between‐study variability and the actual improvement is further reduced by the need to estimate an increasingly large between study covariance matrix; and (iii) when there is little to no between‐study variability, the loss of efficiency due to choosing RE MVMA over FE MVMA increases as p increases. We demonstrate these three features through theory, simulation, and a meta‐analysis of risk factors for non‐Hodgkin lymphoma.     

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta‐analysis and group level studies

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group‐level studies or in meta‐analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log‐odds and arcsine transformations of the estimated probability , both for single‐group studies and in combining results from several groups or studies in meta‐analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta‐analysis and result in abysmal coverage of the combined effect for large K. We also propose bias‐correction for the arcsine transformation. Our simulations demonstrate that this bias‐correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta‐analyses of prevalence.     

Assessment of identity disequilibrium and its relation to empirical heterozygosity fitness correlations: a meta‐analysis

Heterozygosity fitness correlations (HFCs) have frequently been used to detect inbreeding depression, under the assumption that genome‐wide heterozygosity is a good proxy for inbreeding. However, meta‐analyses of the association between fitness measures and individual heterozygosity have shown that often either no correlations are observed or the effect sizes are small. One of the reasons for this may be the absence of variance in inbreeding, a requisite for generating general‐effect HFCs. Recent work has highlighted identity disequilibrium (ID) as a measure that may capture variance in the level of inbreeding within a population; however, no thorough assessment of ID in natural populations has been conducted. In this meta‐analysis, we assess the magnitude of ID (as measured by the g₂ statistic) from 50 previously published HFC studies and its relationship to the observed effect sizes of those studies. We then assess how much power the studies had to detect general‐effect HFCs, and the number of markers that would have been needed to generate a high expected correlation (r² = 0.9) between observed heterozygosity and inbreeding. Across the majority of studies, g₂ values were not significantly different than zero. Despite this, we found that the magnitude of g₂ was associated with the average effect sizes observed in a population, even when point estimates were nonsignificant. These low values of g₂ translated into low expected correlations between heterozygosity and inbreeding and suggest that many more markers than typically used are needed to robustly detect HFCs.     

Facultative adjustment of the offspring sex ratio and male attractiveness: a systematic review and meta‐analysis

Females can benefit from mate choice for male traits (e.g. sexual ornaments or body condition) that reliably signal the effect that mating will have on mean offspring fitness. These male‐derived benefits can be due to material and/or genetic effects. The latter include an increase in the attractiveness, hence likely mating success, of sons. Females can potentially enhance any sex‐biased benefits of mating with certain males by adjusting the offspring sex ratio depending on their mate's phenotype. One hypothesis is that females should produce mainly sons when mating with more attractive or higher quality males. Here we perform a meta‐analysis of the empirical literature that has accumulated to test this hypothesis. The mean effect size was small (r = 0.064–0.095; i.e. explaining <1% of variation in offspring sex ratios) but statistically significant in the predicted direction. It was, however, not robust to correction for an apparent publication bias towards significantly positive results. We also examined the strength of the relationship using different indices of male attractiveness/quality that have been invoked by researchers (ornaments, behavioural displays, female preference scores, body condition, male age, body size, and whether a male is a within‐pair or extra‐pair mate). Only ornamentation and body size significantly predicted the proportion of sons produced. We obtained similar results regardless of whether we ran a standard random‐effects meta‐analysis, or a multi‐level, Bayesian model that included a correction for phylogenetic non‐independence. A moderate proportion of the variance in effect sizes (51.6–56.2%) was due to variation that was not attributable to sampling error (i.e. sample size). Much of this non‐sampling error variance was not attributable to phylogenetic effects or high repeatability of effect sizes among species. It was approximately equally attributable to differences (occurring for unknown reasons) in effect sizes among and within studies (25.3, 22.9% of the total variance). There were no significant effects of year of publication or two aspects of study design (experimental/observational or field/laboratory) on reported effect sizes. We discuss various practical reasons and theoretical arguments as to why small effect sizes should be expected, and why there might be relatively high variation among studies. Currently, there are no species where replicated, experimental studies show that mothers adjust the offspring sex ratio in response to a generally preferred male phenotype. Ultimately, we need more experimental studies that test directly whether females produce more sons when mated to relatively more attractive males, and that provide the requisite evidence that their sons have higher mean fitness than their daughters.     

What determines species richness of parasitic organisms? A meta‐analysis across animal,plant and fungal hosts

Although a small set of external factors account for much of the spatial variation in plant and animal diversity, the search continues for general drivers of variation in parasite species richness among host species. Qualitative reviews of existing evidence suggest idiosyncrasies and inconsistent predictive power for all proposed determinants of parasite richness. Here, we provide the first quantitative synthesis of the evidence using a meta‐analysis of 62 original studies testing the relationship between parasite richness across animal, plant and fungal hosts, and each of its four most widely used presumed predictors: host body size, host geographical range size, host population density, and latitude. We uncover three universal predictors of parasite richness across host species, namely host body size, geographical range size and population density, applicable regardless of the taxa considered and independently of most aspects of study design. A proper match in the primary studies between the focal predictor and both the spatial scale of study and the level at which parasite species richness was quantified (i.e. within host populations or tallied across a host species' entire range) also affected the magnitude of effect sizes. By contrast, except for a couple of indicative trends in subsets of the full dataset, there was no strong evidence for an effect of latitude on parasite species richness; where found, this effect ran counter to the general latitude gradient in diversity, with parasite species richness tending to be higher further from the equator. Finally, the meta‐analysis also revealed a negative relationship between the magnitude of effect sizes and the year of publication of original studies (i.e. a time‐lag bias). This temporal bias may be due to the increasing use of phylogenetic correction in comparative analyses of parasite richness over time, as this correction yields more conservative effect sizes. Overall, these findings point to common underlying processes of parasite diversification fundamentally different from those controlling the diversity of free‐living organisms.     

The effect of Bt crops on soil invertebrates: a systematic review and quantitative meta-analysis

The ongoing debate about the ecological effects of Bt-crops calls for thorough reviews about the impact on soil biodiversity and their ecosystem services. Transgenic Bt-crops have been genetically modified by inserting a Bacillus thuriengensis gene so the plant expresses a Cry toxin aimed for insect crop pests. Non-target soil invertebrates are particularly recognized for their contribution to plant nutrient availability and turnover of organic matter and it is therefore relevant to protect these invertebrate taxa. A number of studies have compared the population abundance and biomass of soil invertebrates in agricultural fields planted with genetically modified Bt crops and their conventional counterparts. Here, were review and analyze a selection of studies on Protista, nematodes, Collembola, mites, enchytraeids, and earthworms systematically to empower the evidence for asking the question whether population abundances and biomasses of soil invertebrates are changed by Bt crops compared to conventional crops. 6110 titles were captured, of which 38 studies passed our inclusion criteria, and a final number of 22 publications were subject to data extraction. A database with 2046 records was compiled covering 36 locations and the Bt types Cry1Ab, Cry1Ac, Cry3Bb1 and Cry3Aa. Comparative effect sizes in terms of Hedges’ g were calculated irrespectively of statistical significance of effects of the source studies. Cry effects on populations were compared across the studies in a meta-analysis employing a hierarchical Bayesian approach of weighted data according to the level of replication. The temporal development of effect sizes was modelled, thereby taking into account the variable duration of the field experiments. There was considerable variation among soil invertebrate orders, but the sample size was insufficient and the sample heterogeneity too large to draw any credible conclusions on the effect of Cry at the order level. However, across orders there was no significant effect of Cry on soil invertebrates.

     

Effect of Sibutramine on Weight Loss and Blood Pressure: A Meta‐analysis of Controlled Trials

Objective: Sibutramine causes weight loss by suppressing the appetite and by promoting energy expenditure, but it can also increase blood pressure through a norepinephrine effect. The aim of this study was to provide a comprehensive meta‐analysis of randomized, controlled trials on the effects of sibutramine on blood pressure and weight loss. Research Methods and Procedures: Twenty‐one placebo‐controlled, double‐blind, randomized trials of sibutramine were identified using MEDLINE, EMBASE, and a manual search. The effect sizes of sibutramine on weight and systolic (SBP) and diastolic (DBP) blood pressure changes were estimated. Subgroup analyses were undertaken to explore the relationship between effect sizes and the study characteristics. Results: The effect size of sibutramine on weight change was ?1.00 (?1.17 to ?0.84), whereas the effect sizes on SBP and DBP changes were 0.16 (0.08 to 0.24) and 0.26 (0.18 to 0.33), respectively. By subgroup analysis, the effect sizes on weight loss were significantly larger when the dosage was ≥15 mg. The effect sizes on increased SBP were significantly larger when the initial body weight was ≥92 kg and the age was <44 years; similarly, the effect sizes on increased DBP were significantly larger when the initial weight was ≥92 kg. Discussion: Sibutramine showed a large effect on weight loss. Because blood pressure was found to be increased slightly, but significantly, sibutramine should be used cautiously in patients with borderline or high blood pressure. Additional studies on its effect on blood pressure are needed.     

Meta‐analysis of rare events under the assumption of a homogeneous treatment effect

We studied the performance of several meta‐analysis methods in rare event settings, when the treatment effect is assumed to be homogeneous and baseline prevalences are either homogeneous or heterogeneous. We conducted extensive simulations that included the three most common effect sizes with count data: the odds ratio, the relative risk, and the risk difference. We investigated several important scenarios by varying the level of rareness, the value of the trials’ arms unbalance, and the size of the treatment effect. We found that the Mantel–Haenszel method and the Binomial regression model provided the best results across all the scenarios investigated. The Peto method performed satisfactorily only when the true effect size was not too large and the degree of unbalance moderate. Inverse variance was the least reliable method. The use of a continuity correction factor slightly improved the performance of the inverse variance method but deteriorated that of the Peto and Mantel–Haenszel methods. A method based on median unbiased estimators of the probabilities provided similar results to those obtained when using the inverse variance method with a continuity correction. Therefore, when the treatment effect can be assumed to be homogeneous and for either homogeneous or heterogeneous baseline prevalences, we highly recommend using the Mantel‐Haenszel method without continuity correction (for all the effect sizes) or the Binomial regression model (for the odds ratio only) to meta‐analyze the data.     

The association between Barrett's esophagus and Helicobacter pylori infection: a meta-analysis

Objective: The effect of Helicobacter pylori on Barrett’s esophagus is poorly understood. We conducted a meta‐analysis to summarize the existing literature examining the effect that H. pylori has on Barrett’s esophagus. Design: We performed a comprehensive search to identify studies pertaining to the association between H. pylori and Barrett’s esophagus. We conducted meta‐regression analyses to identify sources of variation in the effect of H. pylori on Barrett’s esophagus. Results: Our analysis included a total of 49 studies that examined the effect of H. pylori on Barrett’s esophagus and seven studies that examined the effect of cag A positivity on Barrett’s esophagus. Overall, H. pylori, and even more so cag A, tended to be protective for Barrett’s esophagus in most studies; however, there was obvious heterogeneity across studies. The effect of H. pylori on Barrett’s esophagus varied by geographic location and in the presence of selection and information biases. Only four studies were found without obvious selection and information bias, and these showed a protective effect of H. pylori on Barrett’s esophagus (Relative risk = 0.46 [95% CI: 0.35, 0.60]). Conclusions: Estimates for the effect of H. pylori on Barrett’s esophagus were heterogeneous across studies. We identified selection and information bias as potential sources of this heterogeneity. Few studies without obvious selection and information bias have been conducted to examine the effect of H. pylori on Barrett’s esophagus, but in these, H. pylori infection is associated with a reduced risk of Barrett’s esophagus.     

Response misclassification in studies on bilateral diseases

Misclassification in binary outcomes can severely bias effect estimates of regression models when the models are naively applied to error‐prone data. Here, we discuss response misclassification in studies on the special class of bilateral diseases. Such diseases can affect neither, one, or both entities of a paired organ, for example, the eyes or ears. If measurements are available on both organ entities, disease occurrence in a person is often defined as disease occurrence in at least one entity. In this setting, there are two reasons for response misclassification: (a) ignorance of missing disease assessment in one of the two entities and (b) error‐prone disease assessment in the single entities. We investigate the consequences of ignoring both types of response misclassification and present an approach to adjust the bias from misclassification by optimizing an adequate likelihood function. The inherent modelling assumptions and problems in case of entity‐specific misclassification are discussed. This work was motivated by studies on age‐related macular degeneration (AMD), a disease that can occur separately in each eye of a person. We illustrate and discuss the proposed analysis approach based on real‐world data of a study on AMD and simulated data.